Sonar-Based Human Leg Localization Using Chaos Enhanced Dynamic Neighborhood Learning-Based GSA Aided sNDT Algorithm
Pritam Paral, Amitava Chatterjee, Anjan Rakshit, Sankar Kumar Pal · IEEE Transactions on Instrumentation and Measurement · 2022
The present paper proposes a new human leg localization algorithm using ultrasonic sensors in human-robot coexisting environments. The algorithm estimates the motion of a human leg pair between two successive sonar scans by using a newstatic cluster eliminationmethod, anedge feature based leg recognitionalgorithm and an advanced scan matching technique. We also propose a novel, robust approach to overcomebad initializationproblem in sonar scan matching, by introducing a metaheuristic search based optimization algorithm for the sonar NDT (sNDT) method. The recently proposed dynamic neighborhood learning-based GSA (DNLGSA) has been successfully utilized in real-life scenario to solve this problem. The work also proposes a new chaos enhanced DNLGSA (CEDNLGSA) to further improve real-life performance and the proposed novel variant of the sNDT method based on CEDNLGSA, calledChaotic Metaheuristic Search Based sNDT(CMHS-sNDT), has been demonstrated to achieve superior leg detection performance in various real-life case studies, compared to different contemporary state-of-the-art methods.